Preprint / Version 1

Stochastic methodology for estimation of the potential and depleted yield in corn

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DOI:

https://doi.org/10.1590/SciELOPreprints.6698

Keywords:

Simulation, probability distribution, agroecological zone

Abstract

The objective of this research was to compare four methodologies of parameters simulation used in the corn potential and depleted yield in Rio Grande do Sul State. Had been used the daily mean air temperature, isolation and rain precipitation of sixteen localities of the Rio Grande do Sul State, as changeable of entrance in the modified model of the agroecological zone considered by De Wit. The data base was formed by 100 simulated values of the variable in each one of the eighth dates proposals (October 1st, October 11th, October 21st, November 1st, November 11th, November 21st, December 1st, December 11th). The data had been through four cases of simulation: (i) average insolation and temperature (normal truncated); (ii) average insolation and temperature (triangular non-symmetrical); (iii) average insolation and temperature (triangular symmetrical) e (IV) insolation (triangular symmetrical). To verify was that: (i) the adaptation of the method (considered for De Wit) of the agroecological zone makes possible to define the order of magnitude of the maize potential and depleted productivities, in Rio Grande do Sul State; (ii) the random procedure process an in agreement variability time of sowing and evaluated place; (iii) the procedure (b) average insolation and temperature (triangular anti-symmetrical) and (d) insolation (triangular symmetrical) does not diverge how much the classification, being that the last one overestimates the values of potential and depleted productivity.

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Author Biography

Dr., Senior Director Biologicals LATAM na Indigo

Pesquisador Sênior

Posted

09/01/2023

How to Cite

Bonnecarrère, R. A. G., Dourado Neto, D., Silva, N. da R., & Martin, T. (2023). Stochastic methodology for estimation of the potential and depleted yield in corn. In SciELO Preprints. https://doi.org/10.1590/SciELOPreprints.6698

Section

Agricultural Sciences

Plaudit

Data statement

  • The research data is contained in the manuscript